code: def test_image_embedding_forward_runs_with_inputs(
      image_embeddings, image_params_dict
  ):
      batch_size = 2
      feature_dim = image_params_dict["feature_size"]
      image_feature = torch.randn(batch_size, feature_dim)
      image_location = torch.randn(batch_size, 4)
      image_embeddings(image_feature, image_location)
  
imports: import copy
  import pytest
  import torch
  from torch.testing import assert_allclose
  from transformers import AutoModel
  from transformers.models.bert.configuration_bert import BertConfig
  from transformers.models.bert.modeling_bert import BertEmbeddings
  from transformers.models.albert.configuration_albert import AlbertConfig
  from transformers.models.albert.modeling_albert import AlbertEmbeddings
  from allennlp.common import Params, FromParams
  from allennlp.modules.transformer import TransformerEmbeddings, ImageFeatureEmbeddings, TransformerModule
label_desc: Use image node_id 17 for calling a global function with example usage: test_image_embedding_forward_runs_with_inputs(image_embeddings, image_params_dict) without return types